template<typename Architecture_t>
class TMVA::DNN::CNN::TConvLayer< Architecture_t >

Definition at line 43 of file ConvLayer.h.

Public Types
using	Matrix_t = typename Architecture_t::Matrix_t

using	Scalar_t = typename Architecture_t::Scalar_t

Public Member Functions
	TConvLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNRows, size_t WeightsNCols, size_t BiasesNRows, size_t BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init, size_t FilterDepth, size_t FilterHeight, size_t FilterWidth, size_t StrideRows, size_t StrideCols, size_t PaddingHeight, size_t PaddingWidth, Scalar_t DropoutProbability, EActivationFunction f, ERegularization Reg, Scalar_t WeightDecay)
	Constructor. More...

	TConvLayer (TConvLayer< Architecture_t > *layer)
	Copy the conv layer provided as a pointer. More...

	TConvLayer (const TConvLayer &)
	Copy constructor. More...

	~TConvLayer ()
	Destructor. More...

virtual void	AddWeightsXMLTo (void *parent)
	Writes the information and the weights about the layer in an XML node. More...

void	Backward (std::vector< Matrix_t > &gradients_backward, const std::vector< Matrix_t > &activations_backward, std::vector< Matrix_t > &inp1, std::vector< Matrix_t > &inp2)
	Compute weight, bias and activation gradients. More...

void	Forward (std::vector< Matrix_t > &input, bool applyDropout=false)
	Computes activation of the layer for the given input. More...

EActivationFunction	GetActivationFunction () const

const std::vector< Matrix_t > &	GetDerivatives () const

std::vector< Matrix_t > &	GetDerivatives ()

Matrix_t &	GetDerivativesAt (size_t i)

const Matrix_t &	GetDerivativesAt (size_t i) const

Scalar_t	GetDropoutProbability () const

size_t	GetFilterDepth () const
	Getters. More...

size_t	GetFilterHeight () const

size_t	GetFilterWidth () const

size_t	GetNLocalViewPixels () const

size_t	GetNLocalViews () const

size_t	GetPaddingHeight () const

size_t	GetPaddingWidth () const

ERegularization	GetRegularization () const

size_t	GetStrideCols () const

size_t	GetStrideRows () const

Scalar_t	GetWeightDecay () const

void	Print () const
	Prints the info about the layer. More...

virtual void	ReadWeightsFromXML (void *parent)
	Read the information and the weights about the layer from XML node. More...

Public Member Functions inherited from TMVA::DNN::VGeneralLayer< Architecture_t >
	VGeneralLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNSlices, size_t WeightsNRows, size_t WeightsNCols, size_t BiasesNSlices, size_t BiasesNRows, size_t BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init)
	Constructor. More...

	VGeneralLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNSlices, std::vector< size_t > WeightsNRows, std::vector< size_t > WeightsNCols, size_t BiasesNSlices, std::vector< size_t > BiasesNRows, std::vector< size_t > BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init)
	General Constructor with different weights dimension. More...

	VGeneralLayer (VGeneralLayer< Architecture_t > *layer)
	Copy the layer provided as a pointer. More...

	VGeneralLayer (const VGeneralLayer &)
	Copy Constructor. More...

virtual	~VGeneralLayer ()
	Virtual Destructor. More...

void	CopyBiases (const std::vector< Matrix_t > &otherBiases)
	Copies the biases provided as an input. More...

void	CopyWeights (const std::vector< Matrix_t > &otherWeights)
	Copies the weights provided as an input. More...

const std::vector< Matrix_t > &	GetActivationGradients () const

std::vector< Matrix_t > &	GetActivationGradients ()

Matrix_t &	GetActivationGradientsAt (size_t i)

const Matrix_t &	GetActivationGradientsAt (size_t i) const

size_t	GetBatchSize () const
	Getters. More...

const std::vector< Matrix_t > &	GetBiases () const

std::vector< Matrix_t > &	GetBiases ()

const Matrix_t &	GetBiasesAt (size_t i) const

Matrix_t &	GetBiasesAt (size_t i)

const std::vector< Matrix_t > &	GetBiasGradients () const

std::vector< Matrix_t > &	GetBiasGradients ()

const Matrix_t &	GetBiasGradientsAt (size_t i) const

Matrix_t &	GetBiasGradientsAt (size_t i)

size_t	GetDepth () const

size_t	GetHeight () const

EInitialization	GetInitialization () const

size_t	GetInputDepth () const

size_t	GetInputHeight () const

size_t	GetInputWidth () const

const std::vector< Matrix_t > &	GetOutput () const

std::vector< Matrix_t > &	GetOutput ()

Matrix_t &	GetOutputAt (size_t i)

const Matrix_t &	GetOutputAt (size_t i) const

const std::vector< Matrix_t > &	GetWeightGradients () const

std::vector< Matrix_t > &	GetWeightGradients ()

const Matrix_t &	GetWeightGradientsAt (size_t i) const

Matrix_t &	GetWeightGradientsAt (size_t i)

const std::vector< Matrix_t > &	GetWeights () const

std::vector< Matrix_t > &	GetWeights ()

const Matrix_t &	GetWeightsAt (size_t i) const

Matrix_t &	GetWeightsAt (size_t i)

size_t	GetWidth () const

void	Initialize ()
	Initialize the weights and biases according to the given initialization method. More...

bool	IsTraining () const

void	ReadMatrixXML (void node, const char name, Matrix_t &matrix)

void	SetBatchSize (size_t batchSize)
	Setters. More...

void	SetDepth (size_t depth)

void	SetHeight (size_t height)

void	SetInputDepth (size_t inputDepth)

void	SetInputHeight (size_t inputHeight)

void	SetInputWidth (size_t inputWidth)

void	SetIsTraining (bool isTraining)

void	SetWidth (size_t width)

void	Update (const Scalar_t learningRate)
	Updates the weights and biases, given the learning rate. More...

void	UpdateBiases (const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)
	Updates the biases, given the gradients and the learning rate. More...

void	UpdateBiasGradients (const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)
	Updates the bias gradients, given some other weight gradients and learning rate. More...

void	UpdateWeightGradients (const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)
	Updates the weight gradients, given some other weight gradients and learning rate. More...

void	UpdateWeights (const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)
	Updates the weights, given the gradients and the learning rate,. More...

void	WriteMatrixToXML (void node, const char name, const Matrix_t &matrix)

void	WriteTensorToXML (void node, const char name, const std::vector< Matrix_t > &tensor)
	helper functions for XML More...

Private Attributes
std::vector< int >	fBackwardIndices
	Vector of indices used for a fast Im2Col in backward pass. More...

std::vector< Matrix_t >	fDerivatives
	First fDerivatives of the activations of this layer. More...

Scalar_t	fDropoutProbability
	Probability that an input is active. More...

EActivationFunction	fF
	Activation function of the layer. More...

size_t	fFilterDepth
	The depth of the filter. More...

size_t	fFilterHeight
	The height of the filter. More...

size_t	fFilterWidth
	The width of the filter. More...

std::vector< int >	fForwardIndices
	Vector of indices used for a fast Im2Col in forward pass. More...

size_t	fNLocalViewPixels
	The number of pixels in one local image view. More...

size_t	fNLocalViews
	The number of local views in one image. More...

size_t	fPaddingHeight
	The number of zero layers added top and bottom of the input. More...

size_t	fPaddingWidth
	The number of zero layers left and right of the input. More...

ERegularization	fReg
	The regularization method. More...

size_t	fStrideCols
	The number of column pixels to slid the filter each step. More...

size_t	fStrideRows
	The number of row pixels to slid the filter each step. More...

Scalar_t	fWeightDecay
	The weight decay. More...

Additional Inherited Members
Protected Attributes inherited from TMVA::DNN::VGeneralLayer< Architecture_t >
std::vector< Matrix_t >	fActivationGradients
	Gradients w.r.t. the activations of this layer. More...

size_t	fBatchSize
	Batch size used for training and evaluation. More...

std::vector< Matrix_t >	fBiases
	The biases associated to the layer. More...

std::vector< Matrix_t >	fBiasGradients
	Gradients w.r.t. the bias values of the layer. More...

size_t	fDepth
	The depth of the layer. More...

size_t	fHeight
	The height of the layer. More...

EInitialization	fInit
	The initialization method. More...

size_t	fInputDepth
	The depth of the previous layer or input. More...

size_t	fInputHeight
	The height of the previous layer or input. More...

size_t	fInputWidth
	The width of the previous layer or input. More...

bool	fIsTraining
	Flag indicatig the mode. More...

std::vector< Matrix_t >	fOutput
	Activations of this layer. More...

std::vector< Matrix_t >	fWeightGradients
	Gradients w.r.t. the weights of the layer. More...

std::vector< Matrix_t >	fWeights
	The weights associated to the layer. More...

size_t	fWidth
	The width of this layer. More...

#include <TMVA/DNN/CNN/ConvLayer.h>

Inheritance diagram for TMVA::DNN::CNN::TConvLayer< Architecture_t >:

[legend]

Member Typedef Documentation

◆ Matrix_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::Matrix_t = typename Architecture_t::Matrix_t

Definition at line 45 of file ConvLayer.h.

◆ Scalar_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::Scalar_t = typename Architecture_t::Scalar_t

Definition at line 46 of file ConvLayer.h.

Constructor & Destructor Documentation

◆ TConvLayer() [1/3]

template<typename Architecture_t >

TMVA::DNN::CNN::TConvLayer< Architecture_t >::TConvLayer	(	size_t	BatchSize,
		size_t	InputDepth,
		size_t	InputHeight,
		size_t	InputWidth,
		size_t	Depth,
		size_t	Height,
		size_t	Width,
		size_t	WeightsNRows,
		size_t	WeightsNCols,
		size_t	BiasesNRows,
		size_t	BiasesNCols,
		size_t	OutputNSlices,
		size_t	OutputNRows,
		size_t	OutputNCols,
		EInitialization	Init,
		size_t	FilterDepth,
		size_t	FilterHeight,
		size_t	FilterWidth,
		size_t	StrideRows,
		size_t	StrideCols,
		size_t	PaddingHeight,
		size_t	PaddingWidth,
		Scalar_t	DropoutProbability,
		EActivationFunction	f,
		ERegularization	Reg,
		Scalar_t	WeightDecay
	)

Constructor.

Definition at line 147 of file ConvLayer.h.

◆ TConvLayer() [2/3]

template<typename Architecture_t >

TMVA::DNN::CNN::TConvLayer< Architecture_t >::TConvLayer ( TConvLayer< Architecture_t > * layer )

Copy the conv layer provided as a pointer.

Definition at line 170 of file ConvLayer.h.

◆ TConvLayer() [3/3]

template<typename Architecture_t >

TMVA::DNN::CNN::TConvLayer< Architecture_t >::TConvLayer ( const TConvLayer< Architecture_t > & convLayer )

Copy constructor.

Definition at line 193 of file ConvLayer.h.

◆ ~TConvLayer()

template<typename Architecture_t >

TMVA::DNN::CNN::TConvLayer< Architecture_t >::~TConvLayer ( )

Destructor.

Definition at line 212 of file ConvLayer.h.

Member Function Documentation

◆ AddWeightsXMLTo()

template<typename Architecture_t >

void TMVA::DNN::CNN::TConvLayer< Architecture_t >::AddWeightsXMLTo ( void * parent )

virtual

Writes the information and the weights about the layer in an XML node.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 321 of file ConvLayer.h.

◆ Backward()

template<typename Architecture_t >

auto TMVA::DNN::CNN::TConvLayer< Architecture_t >::Backward	(	std::vector< Matrix_t > &	gradients_backward,
		const std::vector< Matrix_t > &	activations_backward,
		std::vector< Matrix_t > &	inp1,
		std::vector< Matrix_t > &	inp2
	)

virtual

Compute weight, bias and activation gradients.

Uses the precomputed first partial derviatives of the activation function computed during forward propagation and modifies them. Must only be called directly at the corresponding call to Forward(...).

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 284 of file ConvLayer.h.

◆ Forward()

template<typename Architecture_t >

auto TMVA::DNN::CNN::TConvLayer< Architecture_t >::Forward	(	std::vector< Matrix_t > &	input,
		bool	applyDropout = `false`
	)

virtual

Computes activation of the layer for the given input.

The input must be in 3D tensor form with the different matrices corresponding to different events in the batch. Computes activations as well as the first partial derivative of the activation function at those activations.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 218 of file ConvLayer.h.

◆ GetActivationFunction()

template<typename Architecture_t>

EActivationFunction TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetActivationFunction ( ) const

inline

Definition at line 137 of file ConvLayer.h.

◆ GetDerivatives() [1/2]

template<typename Architecture_t>

const std::vector<Matrix_t>& TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetDerivatives ( ) const

inline

Definition at line 131 of file ConvLayer.h.

◆ GetDerivatives() [2/2]

template<typename Architecture_t>

std::vector<Matrix_t>& TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetDerivatives ( )

inline

Definition at line 132 of file ConvLayer.h.

◆ GetDerivativesAt() [1/2]

template<typename Architecture_t>

Matrix_t& TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetDerivativesAt ( size_t i )

inline

Definition at line 134 of file ConvLayer.h.

◆ GetDerivativesAt() [2/2]

template<typename Architecture_t>

const Matrix_t& TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetDerivativesAt ( size_t i ) const

inline

Definition at line 135 of file ConvLayer.h.

◆ GetDropoutProbability()

template<typename Architecture_t>

Scalar_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetDropoutProbability ( ) const

inline

Definition at line 129 of file ConvLayer.h.

◆ GetFilterDepth()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetFilterDepth ( ) const

inline

Getters.

Definition at line 116 of file ConvLayer.h.

◆ GetFilterHeight()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetFilterHeight ( ) const

inline

Definition at line 117 of file ConvLayer.h.

◆ GetFilterWidth()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetFilterWidth ( ) const

inline

Definition at line 118 of file ConvLayer.h.

◆ GetNLocalViewPixels()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetNLocalViewPixels ( ) const

inline

Definition at line 126 of file ConvLayer.h.

◆ GetNLocalViews()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetNLocalViews ( ) const

inline

Definition at line 127 of file ConvLayer.h.

◆ GetPaddingHeight()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetPaddingHeight ( ) const

inline

Definition at line 123 of file ConvLayer.h.

◆ GetPaddingWidth()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetPaddingWidth ( ) const

inline

Definition at line 124 of file ConvLayer.h.

◆ GetRegularization()

template<typename Architecture_t>

ERegularization TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetRegularization ( ) const

inline

Definition at line 138 of file ConvLayer.h.

◆ GetStrideCols()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetStrideCols ( ) const

inline

Definition at line 121 of file ConvLayer.h.

◆ GetStrideRows()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetStrideRows ( ) const

inline

Definition at line 120 of file ConvLayer.h.

◆ GetWeightDecay()

template<typename Architecture_t>

Scalar_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetWeightDecay ( ) const

inline

Definition at line 139 of file ConvLayer.h.

◆ Print()

template<typename Architecture_t >

auto TMVA::DNN::CNN::TConvLayer< Architecture_t >::Print ( ) const

virtual

Prints the info about the layer.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 301 of file ConvLayer.h.

◆ ReadWeightsFromXML()

template<typename Architecture_t >

void TMVA::DNN::CNN::TConvLayer< Architecture_t >::ReadWeightsFromXML ( void * parent )

virtual

Read the information and the weights about the layer from XML node.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 346 of file ConvLayer.h.

Member Data Documentation

◆ fBackwardIndices

template<typename Architecture_t>

std::vector<int> TMVA::DNN::CNN::TConvLayer< Architecture_t >::fBackwardIndices

private

Vector of indices used for a fast Im2Col in backward pass.

Definition at line 67 of file ConvLayer.h.

◆ fDerivatives

template<typename Architecture_t>

std::vector<Matrix_t> TMVA::DNN::CNN::TConvLayer< Architecture_t >::fDerivatives

private

First fDerivatives of the activations of this layer.

Definition at line 64 of file ConvLayer.h.

◆ fDropoutProbability

template<typename Architecture_t>

Scalar_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fDropoutProbability

private

Probability that an input is active.

Definition at line 62 of file ConvLayer.h.

◆ fF

template<typename Architecture_t>

EActivationFunction TMVA::DNN::CNN::TConvLayer< Architecture_t >::fF

private

Activation function of the layer.

Definition at line 70 of file ConvLayer.h.

◆ fFilterDepth

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fFilterDepth

private

The depth of the filter.

Definition at line 49 of file ConvLayer.h.

◆ fFilterHeight

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fFilterHeight

private

The height of the filter.

Definition at line 50 of file ConvLayer.h.

◆ fFilterWidth

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fFilterWidth

private

The width of the filter.

Definition at line 51 of file ConvLayer.h.

◆ fForwardIndices

template<typename Architecture_t>

std::vector<int> TMVA::DNN::CNN::TConvLayer< Architecture_t >::fForwardIndices

private

Vector of indices used for a fast Im2Col in forward pass.

Definition at line 66 of file ConvLayer.h.

◆ fNLocalViewPixels

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fNLocalViewPixels

private

The number of pixels in one local image view.

Definition at line 59 of file ConvLayer.h.

◆ fNLocalViews

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fNLocalViews

private

The number of local views in one image.

Definition at line 60 of file ConvLayer.h.

◆ fPaddingHeight

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fPaddingHeight

private

The number of zero layers added top and bottom of the input.

Definition at line 56 of file ConvLayer.h.

◆ fPaddingWidth

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fPaddingWidth

private

The number of zero layers left and right of the input.

Definition at line 57 of file ConvLayer.h.

◆ fReg

template<typename Architecture_t>

ERegularization TMVA::DNN::CNN::TConvLayer< Architecture_t >::fReg

private

The regularization method.

Definition at line 71 of file ConvLayer.h.

◆ fStrideCols

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fStrideCols

private

The number of column pixels to slid the filter each step.

Definition at line 54 of file ConvLayer.h.

◆ fStrideRows

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fStrideRows

private

The number of row pixels to slid the filter each step.

Definition at line 53 of file ConvLayer.h.

◆ fWeightDecay

template<typename Architecture_t>

Scalar_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fWeightDecay

private

The weight decay.

Definition at line 72 of file ConvLayer.h.

Libraries for TMVA::DNN::CNN::TConvLayer< Architecture_t >:

[legend]

template<typename Architecture_t> class TMVA::DNN::CNN::TConvLayer< Architecture_t >

Public Types

Public Member Functions

Private Attributes

Additional Inherited Members

Member Typedef Documentation

◆ Matrix_t

◆ Scalar_t

Constructor & Destructor Documentation

◆ TConvLayer() [1/3]

◆ TConvLayer() [2/3]

◆ TConvLayer() [3/3]

◆ ~TConvLayer()

Member Function Documentation

◆ AddWeightsXMLTo()

◆ Backward()

◆ Forward()

◆ GetActivationFunction()

◆ GetDerivatives() [1/2]

◆ GetDerivatives() [2/2]

◆ GetDerivativesAt() [1/2]

◆ GetDerivativesAt() [2/2]

◆ GetDropoutProbability()

◆ GetFilterDepth()

◆ GetFilterHeight()

◆ GetFilterWidth()

◆ GetNLocalViewPixels()

◆ GetNLocalViews()

◆ GetPaddingHeight()

◆ GetPaddingWidth()

◆ GetRegularization()

◆ GetStrideCols()

◆ GetStrideRows()

◆ GetWeightDecay()

◆ Print()

◆ ReadWeightsFromXML()

Member Data Documentation

◆ fBackwardIndices

◆ fDerivatives

◆ fDropoutProbability

◆ fF

◆ fFilterDepth

◆ fFilterHeight

◆ fFilterWidth

◆ fForwardIndices

◆ fNLocalViewPixels

◆ fNLocalViews

◆ fPaddingHeight

◆ fPaddingWidth

◆ fReg

◆ fStrideCols

◆ fStrideRows

◆ fWeightDecay

template<typename Architecture_t>
class TMVA::DNN::CNN::TConvLayer< Architecture_t >